Python爬虫框架之Scrapy
性能相关
在编写爬虫时，性能的消耗主要在IO请求中，当单进程单线程模式下请求URL时必然会引起等待，从而使得请求整体变慢。
那么如何编写出高效的程序。
import requests def fetch_async(url): response = requests.get(url) return response url_list = ['http://www.github.com', 'http://www.bing.com'] for url in url_list: fetch_async(url)
from concurrent.futures import ThreadPoolExecutor import requests def fetch_async(url): response = requests.get(url) return response url_list = ['http://www.github.com', 'http://www.bing.com'] pool = ThreadPoolExecutor(5) for url in url_list: pool.submit(fetch_async, url) pool.shutdown(wait=True)
from concurrent.futures import ThreadPoolExecutor import requests def fetch_async(url): response = requests.get(url) return response def callback(future): print(future.result()) url_list = ['http://www.github.com', 'http://www.bing.com'] pool = ThreadPoolExecutor(5) for url in url_list: v = pool.submit(fetch_async, url) v.add_done_callback(callback) pool.shutdown(wait=True)
from concurrent.futures import ProcessPoolExecutor import requests def fetch_async(url): response = requests.get(url) return response url_list = ['http://www.github.com', 'http://www.bing.com'] pool = ProcessPoolExecutor(5) for url in url_list: pool.submit(fetch_async, url) pool.shutdown(wait=True)
from concurrent.futures import ProcessPoolExecutor import requests def fetch_async(url): response = requests.get(url) return response def callback(future): print(future.result()) url_list = ['http://www.github.com', 'http://www.bing.com'] pool = ProcessPoolExecutor(5) for url in url_list: v = pool.submit(fetch_async, url) v.add_done_callback(callback) pool.shutdown(wait=True)
通过上述代码均可以完成对请求性能的提高，对于多线程和多进行的缺点是在IO阻塞时会造成了线程和进程的浪费，所以异步IO会是首选：
import asyncio @asyncio.coroutine def func1(): print('before...func1......') yield from asyncio.sleep(5) print('end...func1......') tasks = [func1(), func1()] loop = asyncio.get_event_loop() loop.run_until_complete(asyncio.gather(*tasks)) loop.close()
import asyncio @asyncio.coroutine def fetch_async(host, url='/'): print(host, url) reader, writer = yield from asyncio.open_connection(host, 80) request_header_content = """GET %s HTTP/1.0\r\nHost: %s\r\n\r\n""" % (url, host,) request_header_content = bytes(request_header_content, encoding='utf-8') writer.write(request_header_content) yield from writer.drain() text = yield from reader.read() print(host, url, text) writer.close() tasks = [ fetch_async('www.cnblogs.com', '/wupeiqi/'), fetch_async('dig.chouti.com', '/pic/show?nid=4073644713430508&lid=10273091') ] loop = asyncio.get_event_loop() results = loop.run_until_complete(asyncio.gather(*tasks)) loop.close()
import aiohttp import asyncio @asyncio.coroutine def fetch_async(url): print(url) response = yield from aiohttp.request('GET', url) # data = yield from response.read() # print(url, data) print(url, response) response.close() tasks = [fetch_async('http://www.google.com/'), fetch_async('http://www.chouti.com/')] event_loop = asyncio.get_event_loop() results = event_loop.run_until_complete(asyncio.gather(*tasks)) event_loop.close()
import asyncio import requests @asyncio.coroutine def fetch_async(func, *args): loop = asyncio.get_event_loop() future = loop.run_in_executor(None, func, *args) response = yield from future print(response.url, response.content) tasks = [ fetch_async(requests.get, 'http://www.cnblogs.com/wupeiqi/'), fetch_async(requests.get, 'http://dig.chouti.com/pic/show?nid=4073644713430508&lid=10273091') ] loop = asyncio.get_event_loop() results = loop.run_until_complete(asyncio.gather(*tasks)) loop.close()
import gevent import requests from gevent import monkey monkey.patch_all() def fetch_async(method, url, req_kwargs): print(method, url, req_kwargs) response = requests.request(method=method, url=url, **req_kwargs) print(response.url, response.content) # ##### 发送请求 ##### gevent.joinall([ gevent.spawn(fetch_async, method='get', url='https://www.python.org/', req_kwargs={}), gevent.spawn(fetch_async, method='get', url='https://www.yahoo.com/', req_kwargs={}), gevent.spawn(fetch_async, method='get', url='https://github.com/', req_kwargs={}), ]) # ##### 发送请求（协程池控制最大协程数量） ##### # from gevent.pool import Pool # pool = Pool(None) # gevent.joinall([ # pool.spawn(fetch_async, method='get', url='https://www.python.org/', req_kwargs={}), # pool.spawn(fetch_async, method='get', url='https://www.yahoo.com/', req_kwargs={}), # pool.spawn(fetch_async, method='get', url='https://www.github.com/', req_kwargs={}), # ])
import grequests request_list = [ grequests.get('http://httpbin.org/delay/1', timeout=0.001), grequests.get('http://fakedomain/'), grequests.get('http://httpbin.org/status/500') ] # ##### 执行并获取响应列表 ##### # response_list = grequests.map(request_list) # print(response_list) # ##### 执行并获取响应列表（处理异常） ##### # def exception_handler(request, exception): # print(request,exception) # print("Request failed") # response_list = grequests.map(request_list, exception_handler=exception_handler) # print(response_list)
from twisted.web.client import getPage from twisted.internet import reactor REV_COUNTER = 0 REQ_COUNTER = 0 def callback(contents): print(contents,) global REV_COUNTER REV_COUNTER += 1 if REV_COUNTER == REQ_COUNTER: reactor.stop() url_list = ['http://www.bing.com', 'http://www.baidu.com', ] REQ_COUNTER = len(url_list) for url in url_list: deferred = getPage(bytes(url, encoding='utf8')) deferred.addCallback(callback) reactor.run()
#!/usr/bin/env python # -*- coding:utf-8 -*- from twisted.internet import defer from twisted.web.client import getPage from twisted.internet import reactor @defer.inlineCallbacks def task(url): url = url while url: ret = getPage(bytes(url, encoding='utf8')) ret.addCallback(one_done) url = yield ret i = 0 def one_done(arg): global i i += 1 if i == 10: return print('one', arg) return 'http://www.cnblogs.com' @defer.inlineCallbacks def task_list(): start_url_list = [ 'http://www.cnblogs.com', ] defer_list = [] for url in start_url_list: deferObj = task(url) defer_list.append(deferObj) yield defer.DeferredList(defer_list) def all_done(arg): print('done', arg) reactor.stop() if __name__ == '__main__': d = task_list() print(type(d)) d.addBoth(all_done) reactor.run()
#!/usr/bin/env python # -*- coding:utf-8 -*- from tornado.httpclient import AsyncHTTPClient from tornado.httpclient import HTTPRequest from tornado import ioloop def handle_response(response): if response.error: print("Error:", response.error) else: print(response.body) # 方法同twisted # ioloop.IOLoop.current().stop() def func(): url_list = [ 'http://www.google.com', 'http://127.0.0.1:8000/test2/', ] for url in url_list: print(url) http_client = AsyncHTTPClient() http_client.fetch(HTTPRequest(url), handle_response) ioloop.IOLoop.current().add_callback(func) ioloop.IOLoop.current().start()
以上均是Python内置以及第三方模块提供异步IO请求模块，使用简便大大提高效率，而对于异步IO请求的本质则是【非阻塞Socket】+【IO多路复用】：
import select import socket class HttpRequest(object): def __init__(self, sk, host, callback): self.sk = sk self.host = host self.callback = callback def fileno(self): return self.sk.fileno() class AsyncRequest(object): def __init__(self): self.conn = [] self.connection = [] def add_request(self, host, callback): try: sk = socket.socket() sk.setblocking(False) sk.connect((host, 80, )) except BlockingIOError as e: pass request = HttpRequest(sk, host, callback) self.conn.append(request) self.connection.append(request) def running(self): while True: # select并不仅仅只能监听socket套接字对象 # 再自定义对象中实现fileno()方法, 并返回socket文件描述符对象即可 return socket_obj.fileno() r_list, w_list, e_list = select.select(self.conn, self.connection, self.conn, 0.05) for w in w_list: # w_list 表示连接上的请求 http_msg = "GET / HTTP/1.0\r\nHost:%s\r\n\r\n" % (w.host,) w.sk.send(bytes(http_msg, encoding='utf-8')) self.connection.remove(w) for r in r_list: # r_list 表示有数据返回 data = bytes() while True: try: recv = r.sk.recv(8096) data += recv except Exception as e: break r.callback(data) r.sk.close() self.conn.remove(r) if len(self.conn) == 0: break def func1(data): print(data) def func2(data): print(data) url_list = [ {'host': 'www.baidu.com', 'callback': func1}, {'host': 'www.cnblogs.com', 'callback': func2}, {'host': 'www.huaban.com', 'callback': func2}, ] async_obj = AsyncRequest() for item in url_list: async_obj.add_request(item['host'], item['callback']) async_obj.running()
Scrapy介绍及安装
Scrapy是一个为了爬取网站数据，提取结构性数据而编写的应用框架。 其可以应用在数据挖掘，信息处理或存储历史数据等一系列的程序中。
其最初是为了页面抓取 (更确切来说, 网络抓取 )所设计的， 也可以应用在获取API所返回的数据(例如 Amazon Associates Web Services ) 或者通用的网络爬虫。Scrapy用途广泛，可以用于数据挖掘、监测和自动化测试。
Scrapy主要包括了以下组件：
- 引擎(Scrapy)
用来处理整个系统的数据流处理, 触发事务(框架核心) - 调度器(Scheduler)
用来接受引擎发过来的请求, 压入队列中, 并在引擎再次请求的时候返回. 可以想像成一个URL（抓取网页的网址或者说是链接）的优先队列, 由它来决定下一个要抓取的网址是什么, 同时去除重复的网址 - 下载器(Downloader)
用于下载网页内容, 并将网页内容返回给蜘蛛(Scrapy下载器是建立在twisted这个高效的异步模型上的) - 爬虫(Spiders)
爬虫是主要干活的, 用于从特定的网页中提取自己需要的信息, 即所谓的实体(Item)。用户也可以从中提取出链接,让Scrapy继续抓取下一个页面 - 项目管道(Pipeline)
负责处理爬虫从网页中抽取的实体，主要的功能是持久化实体、验证实体的有效性、清除不需要的信息。当页面被爬虫解析后，将被发送到项目管道，并经过几个特定的次序处理数据。 - 下载器中间件(Downloader Middlewares)
位于Scrapy引擎和下载器之间的框架，主要是处理Scrapy引擎与下载器之间的请求及响应。 - 爬虫中间件(Spider Middlewares)
介于Scrapy引擎和爬虫之间的框架，主要工作是处理蜘蛛的响应输入和请求输出。 - 调度中间件(Scheduler Middewares)
介于Scrapy引擎和调度之间的中间件，从Scrapy引擎发送到调度的请求和响应。
Scrapy运行流程大概如下：
- 引擎从调度器中取出一个链接(URL)用于接下来的抓取
- 引擎把URL封装成一个请求(Request)传给下载器
- 下载器把资源下载下来，并封装成应答包(Response)
- 爬虫解析Response
- 解析出实体（Item）,则交给实体管道进行进一步的处理
- 解析出的是链接（URL）,则把URL交给调度器等待抓取
Scrapy安装
Linux pip3 install scrapy Windows a. pip3 install wheel b. 下载twisted http://www.lfd.uci.edu/~gohlke/pythonlibs/#twisted c. 进入下载目录，执行 pip3 install Twisted‑17.1.0‑cp35‑cp35m‑win_amd64.whl d. pip3 install scrapy e. 下载并安装pywin32：https://sourceforge.net/projects/pywin32/files/
Scrapy命令及项目结构
1，基本命令
1. scrapy startproject 项目名称 - 在当前目录中创建中创建一个项目文件（类似于Django） 2. scrapy genspider [-t template] <name> <domain> - 创建爬虫应用 如： scrapy gensipider -t basic oldboy oldboy.com scrapy gensipider -t xmlfeed autohome autohome.com.cn PS: 查看所有命令：scrapy gensipider -l 查看模板命令：scrapy gensipider -d 模板名称 3. scrapy list - 展示爬虫应用列表 4. scrapy crawl 爬虫应用名称 - 运行单独爬虫应用
2，项目结构以及应用简介
project_name/ scrapy.cfg project_name/ __init__.py items.py pipelines.py settings.py spiders/ __init__.py 爬虫1.py 爬虫2.py 爬虫3.py
文件说明：
- scrapy.cfg 项目的主配置信息。（真正爬虫相关的配置信息在settings.py文件中）
- items.py 设置数据存储模板，用于结构化数据，如：Django的Model
- pipelines 数据处理行为，如：一般结构化的数据持久化
- settings.py 配置文件，如：递归的层数、并发数，延迟下载等
- spiders 爬虫目录，如：创建文件，编写爬虫规则
注意：一般创建爬虫文件时，以网站域名命名
import scrapy class XiaoHuarSpider(scrapy.spiders.Spider): name = "xiaohuar" # 爬虫名称 ***** allowed_domains = ["xiaohuar.com"] # 允许的域名 start_urls = [ "http://www.xiaohuar.com/hua/", # 其实URL ] def parse(self, response): # 访问起始URL并获取结果后的回调函数
Scrapy初体验
编写 Spider/spider_name.py 文件
import scrapy from scrapy.selector import HtmlXPathSelector from scrapy.http.request import Request class DigSpider(scrapy.Spider): # 爬虫应用的名称，通过此名称启动爬虫命令 name = "dig" # 允许的域名 allowed_domains = ["chouti.com"] # 起始URL start_urls = [ 'http://dig.chouti.com/', ] has_request_set = {} def parse(self, response): print(response.url) hxs = HtmlXPathSelector(response) page_list = hxs.select('//div[@id="dig_lcpage"]//a[re:test(@href, "/all/hot/recent/\d+")]/@href').extract() for page in page_list: page_url = 'http://dig.chouti.com%s' % page key = self.md5(page_url) if key in self.has_request_set: pass else: self.has_request_set[key] = page_url obj = Request(url=page_url, method='GET', callback=self.parse) yield obj @staticmethod def md5(val): import hashlib ha = hashlib.md5() ha.update(bytes(val, encoding='utf-8')) key = ha.hexdigest() return key
执行此文件需
scrapy crawl dig --nolog
对于上述代码重要之处在于：
- Request是一个封装用户请求的类，在回调函数中yield该对象表示继续访问
- HtmlXpathSelector用于结构化HTML代码并提供选择器功能
选择器
#!/usr/bin/env python # -*- coding:utf-8 -*- from scrapy.selector import Selector, HtmlXPathSelector from scrapy.http import HtmlResponse html = """<!DOCTYPE html> <html> <head lang="en"> <meta charset="UTF-8"> <title></title> </head> <body> <ul> <li class="item-"><a id='i1' href="link.html">first item</a></li> <li class="item-0"><a id='i2' href="llink.html">first item</a></li> <li class="item-1"><a href="llink2.html">second item<span>vv</span></a></li> </ul> <div><a href="llink2.html">second item</a></div> </body> </html> """ response = HtmlResponse(url='http://example.com', body=html,encoding='utf-8') # hxs = HtmlXPathSelector(response) # print(hxs) # hxs = Selector(response=response).xpath('//a') # print(hxs) # hxs = Selector(response=response).xpath('//a[2]') # print(hxs) # hxs = Selector(response=response).xpath('//a[@id]') # print(hxs) # hxs = Selector(response=response).xpath('//a[@id="i1"]') # print(hxs) # hxs = Selector(response=response).xpath('//a[@href="link.html"][@id="i1"]') # print(hxs) # hxs = Selector(response=response).xpath('//a[contains(@href, "link")]') # print(hxs) # hxs = Selector(response=response).xpath('//a[starts-with(@href, "link")]') # print(hxs) # hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]') # print(hxs) # hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]/text()').extract() # print(hxs) # hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]/@href').extract() # print(hxs) # hxs = Selector(response=response).xpath('/html/body/ul/li/a/@href').extract() # print(hxs) # hxs = Selector(response=response).xpath('//body/ul/li/a/@href').extract_first() # print(hxs) # ul_list = Selector(response=response).xpath('//body/ul/li') # for item in ul_list: # v = item.xpath('./a/span') # # 或 # # v = item.xpath('a/span') # # 或 # # v = item.xpath('*/a/span') # print(v)
示例
# -*- coding: utf-8 -*- import scrapy from scrapy.selector import HtmlXPathSelector from scrapy.http.request import Request from scrapy.http.cookies import CookieJar from scrapy import FormRequest class ChouTiSpider(scrapy.Spider): # 爬虫应用的名称，通过此名称启动爬虫命令 name = "chouti" # 允许的域名 allowed_domains = ["chouti.com"] cookie_dict = {} has_request_set = {} def start_requests(self): url = 'http://dig.chouti.com/' # return [Request(url=url, callback=self.login)] yield Request(url=url, callback=self.login) def login(self, response): cookie_jar = CookieJar() cookie_jar.extract_cookies(response, response.request) for k, v in cookie_jar._cookies.items(): for i, j in v.items(): for m, n in j.items(): self.cookie_dict[m] = n.value req = Request( url='http://dig.chouti.com/login', method='POST', headers={'Content-Type': 'application/x-www-form-urlencoded; charset=UTF-8'}, body='phone=8615131255089&password=pppppppp&oneMonth=1', cookies=self.cookie_dict, callback=self.check_login ) yield req def check_login(self, response): req = Request( url='http://dig.chouti.com/', method='GET', callback=self.show, cookies=self.cookie_dict, dont_filter=True ) yield req def show(self, response): # print(response) hxs = HtmlXPathSelector(response) news_list = hxs.select('//div[@id="content-list"]/div[@class="item"]') for new in news_list: # temp = new.xpath('div/div[@class="part2"]/@share-linkid').extract() link_id = new.xpath('*/div[@class="part2"]/@share-linkid').extract_first() yield Request( url='http://dig.chouti.com/link/vote?linksId=%s' %(link_id,), method='POST', cookies=self.cookie_dict, callback=self.do_favor ) page_list = hxs.select('//div[@id="dig_lcpage"]//a[re:test(@href, "/all/hot/recent/\d+")]/@href').extract() for page in page_list: page_url = 'http://dig.chouti.com%s' % page import hashlib hash = hashlib.md5() hash.update(bytes(page_url,encoding='utf-8')) key = hash.hexdigest() if key in self.has_request_set: pass else: self.has_request_set[key] = page_url yield Request( url=page_url, method='GET', callback=self.show ) def do_favor(self, response): print(response.text)
注意：settings.py中设置DEPTH_LIMIT = 1来指定"递归"的层数。
Scrapy格式化处理
上述实例只是简单的处理，所以在parse方法中直接处理。如果对于想要获取更多的数据处理，则可以利用Scrapy的items将数据格式化，然后统一交由pipelines来处理。接下来演示一个下载校花网图片的DEMO。
# -*- coding: utf-8 -*- import scrapy import sys import io from xiaohua.items import XiaohuaItem from scrapy.selector import Selector, HtmlXPathSelector from scrapy.http.request import Request sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='gb18030') class XiaohuarSpider(scrapy.Spider): # 爬虫应用的名称，通过此名称启动爬虫命令 name = "xiaohuar" # 允许的域名 allowed_domains = ["xiaohuar.com"] start_urls = ['http://www.xiaohuar.com/hua/'] visited_urls = set() def parse(self, response): # 分析页面 # 找到页面中符合规则的内容（校花图片），保存 # 找到所有的a标签，再访问其他a标签，一层一层的搞下去 hxs1 = Selector(response=response).xpath('//div[@id="list_img"]') # 标签对象列表 for obj in hxs1: img_list = obj.xpath('.//div[@class="img"]') for img in img_list: img_url = img.xpath('.//a/img/@src').extract_first().strip() img_title = img.xpath('.//span[@class="price"]/text()').extract_first().strip() img_obj = XiaohuaItem(title=img_title, href=img_url) yield img_obj hxs = Selector(response=response).xpath( '//a[re:test(@href, "http://www.xiaohuar.com/list-1-\d+.html")]/@href' ).extract() for url in hxs: md5_url = self.encrypt(url) if md5_url not in self.visited_urls: self.visited_urls.add(md5_url) yield Request(url=url, callback=self.parse) def encrypt(self, url): import hashlib hash_obj = hashlib.md5() hash_obj.update(bytes(url, encoding='utf-8')) return hash_obj.hexdigest()
import scrapy class XiaohuaItem(scrapy.Item): # define the fields for your item here like: # name = scrapy.Field() title = scrapy.Field() href = scrapy.Field()
from scrapy.contrib.pipeline.images import ImagesPipeline from scrapy.exceptions import DropItem from scrapy.http.request import Request class XiaohuaPipeline(ImagesPipeline): """ Scrapy 封装了 ImagesPipeline 的管道, 辣么只需要继承一下它, 并重写了俩个方法(名字不可随意修改) 如果你不想使用它, 打开注释掉的内容即可 """ # def process_item(self, item, spider): # img_url = 'http://www.xiaohuar.com{}'.format(item['href']) # print(img_url) # img_name = '{}.jpg'.format(item['title']) # response = requests.get(url=img_url) # with open(os.path.join('image', img_name), 'wb') as f: # f.write(response.content) # # return item def get_media_requests(self, item, info): img_url = 'http://www.xiaohuar.com{}'.format(item['href']) yield Request(img_url) def item_completed(self, results, item, info): # print(results) image_paths = [x['path'] for ok, x in results if ok] if not image_paths: raise DropItem("Item contains no images") item['image_paths'] = image_paths return item
ITEM_PIPELINES = { 'xiaohua.pipelines.XiaohuaPipeline': 300, 'scrapy.contrib.pipeline.images.ImagesPipeline': 1 } # 每行后面的整型值，确定了他们运行的顺序，item按数字从低到高的顺序，通过pipeline，通常将这些数字定义在0-1000范围内。 # 递归深度 DEPTH_LIMIT = 1 # 项目图片下载路径 IMAGES_STORE = 'F:\\python\\spiderTest\\xiaohua\\image'
对于pipeline可以做更多，如下：
from scrapy.exceptions import DropItem class CustomPipeline(object): def __init__(self,v): self.value = v def process_item(self, item, spider): # 操作并进行持久化 # return表示会被后续的pipeline继续处理 return item # 表示将item丢弃，不会被后续pipeline处理 # raise DropItem() @classmethod def from_crawler(cls, crawler): """ 初始化时候，用于创建pipeline对象 :param crawler: :return: """ val = crawler.settings.getint('MMMM') return cls(val) def open_spider(self,spider): """ 爬虫开始执行时，调用 :param spider: :return: """ print('000000') def close_spider(self,spider): """ 爬虫关闭时，被调用 :param spider: :return: """ print('111111')
Scrapy中间件
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爬虫中间件 爬虫中间件是介入到Scrapy的spider处理机制的钩子框架，您可以添加代码来处理发送给 Spiders 的response及spider产生的item和 request。 激活爬虫中间件 要启用 spider中间件，您可以将其加入到 # 在 settings 文件中配置如下，如果值为None即为不启用
SPIDER_MIDDLEWARES = {
'myproject.middlewares.CustomSpiderMiddleware': 543,
'scrapy.contrib.spidermiddleware.offsite.OffsiteMiddleware': None,
}
编写自己的爬虫中间件
class SpiderMiddleware(object): def process_spider_input(self,response, spider): """ 下载完成，执行，然后交给parse处理 :param response: :param spider: :return: """ pass def process_spider_output(self,response, result, spider): """ spider处理完成，返回时调用 :param response: :param result: :param spider: :return: 必须返回包含 Request 或 Item 对象的可迭代对象(iterable) """ return result def process_spider_exception(self,response, exception, spider): """ 异常调用 :param response: :param exception: :param spider: :return: None,继续交给后续中间件处理异常；含 Response 或 Item 的可迭代对象(iterable)，交给调度器或pipeline """ return None def process_start_requests(self,start_requests, spider): """ 爬虫启动时调用 :param start_requests: :param spider: :return: 包含 Request 对象的可迭代对象 """ return start_requests 爬虫中间件 |
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下载中间件 下载器中间件是介于Scrapy的request/response处理的钩子框架。 是用于全局修改Scrapy request和response的一个轻量、底层的系统。 激活下载中间件 要激活下载器中间件组件，将其加入到 # 在 settings 文件中配置， 值为None即为不启用
DOWNLOADER_MIDDLEWARES = {
'myproject.middlewares.CustomDownloaderMiddleware': 543,
'scrapy.contrib.downloadermiddleware.useragent.UserAgentMiddleware': None,
}
编写自己的下载中间件
class DownMiddleware1(object): def process_request(self, request, spider): """ 请求需要被下载时，经过所有下载器中间件的process_request调用 :param request: :param spider: :return: None,继续后续中间件去下载； Response对象，停止process_request的执行，开始执行process_response Request对象，停止中间件的执行，将Request重新调度器 raise IgnoreRequest异常，停止process_request的执行，开始执行process_exception """ pass def process_response(self, request, response, spider): """ spider处理完成，返回时调用 :param response: :param result: :param spider: :return: Response 对象：转交给其他中间件process_response Request 对象：停止中间件，request会被重新调度下载 raise IgnoreRequest 异常：调用Request.errback """ print('response1') return response def process_exception(self, request, exception, spider): """ 当下载处理器(download handler)或 process_request() (下载中间件)抛出异常 :param response: :param exception: :param spider: :return: None：继续交给后续中间件处理异常； Response对象：停止后续process_exception方法 Request对象：停止中间件，request将会被重新调用下载 """ return None |
Scrapy自定制命令
- 在spiders同级创建任意目录，如：commands
- 在其中创建 crawlall.py 文件 （此处文件名就是自定义的命令）
from scrapy.commands import ScrapyCommand from scrapy.utils.project import get_project_settings class Command(ScrapyCommand): requires_project = True def syntax(self): return '[options]' def short_desc(self): return 'Runs all of the spiders' def run(self, args, opts): spider_list = self.crawler_process.spiders.list() for name in spider_list: self.crawler_process.crawl(name, **opts.__dict__) self.crawler_process.start()
- 在settings.py 中添加配置 COMMANDS_MODULE = '项目名称.目录名称'
- 在项目目录执行命令：scrapy crawlall
Scrapy避免重复访问
scrapy默认使用 scrapy.dupefilter.RFPDupeFilter 进行去重，相关配置有：
DUPEFILTER_CLASS = 'scrapy.dupefilter.RFPDupeFilter' DUPEFILTER_DEBUG = False JOBDIR = "保存范文记录的日志路径，如：/root/" # 最终路径为 /root/requests.seen
class RepeatUrl: def __init__(self): self.visited_url = set() @classmethod def from_settings(cls, settings): """ 初始化时，调用 :param settings: :return: """ return cls() def request_seen(self, request): """ 检测当前请求是否已经被访问过 :param request: :return: True表示已经访问过；False表示未访问过 """ if request.url in self.visited_url: return True self.visited_url.add(request.url) return False def open(self): """ 开始爬去请求时，调用 :return: """ print('open replication') def close(self, reason): """ 结束爬虫爬取时，调用 :param reason: :return: """ print('close replication') def log(self, request, spider): """ 记录日志 :param request: :param spider: :return: """ print('repeat', request.url)
Scrapy中Settings
# -*- coding: utf-8 -*- # Scrapy settings for step8_king project # # For simplicity, this file contains only settings considered important or # commonly used. You can find more settings consulting the documentation: # # http://doc.scrapy.org/en/latest/topics/settings.html # http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html # http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html # 1. 爬虫名称 BOT_NAME = 'step8_king' # 2. 爬虫应用路径 SPIDER_MODULES = ['step8_king.spiders'] NEWSPIDER_MODULE = 'step8_king.spiders' # Crawl responsibly by identifying yourself (and your website) on the user-agent # 3. 客户端 user-agent请求头 # USER_AGENT = 'step8_king (+http://www.yourdomain.com)' # Obey robots.txt rules # 4. 禁止爬虫配置 # ROBOTSTXT_OBEY = False # Configure maximum concurrent requests performed by Scrapy (default: 16) # 5. 并发请求数 # CONCURRENT_REQUESTS = 4 # Configure a delay for requests for the same website (default: 0) # See http://scrapy.readthedocs.org/en/latest/topics/settings.html#download-delay # See also autothrottle settings and docs # 6. 延迟下载秒数 # DOWNLOAD_DELAY = 2 # The download delay setting will honor only one of: # 7. 单域名访问并发数，并且延迟下次秒数也应用在每个域名 # CONCURRENT_REQUESTS_PER_DOMAIN = 2 # 单IP访问并发数，如果有值则忽略：CONCURRENT_REQUESTS_PER_DOMAIN，并且延迟下次秒数也应用在每个IP # CONCURRENT_REQUESTS_PER_IP = 3 # Disable cookies (enabled by default) # 8. 是否支持cookie，cookiejar进行操作cookie # COOKIES_ENABLED = True # COOKIES_DEBUG = True # Disable Telnet Console (enabled by default) # 9. Telnet用于查看当前爬虫的信息，操作爬虫等... # 使用telnet ip port ，然后通过命令操作 # TELNETCONSOLE_ENABLED = True # TELNETCONSOLE_HOST = '127.0.0.1' # TELNETCONSOLE_PORT = [6023,] # 10. 默认请求头 # Override the default request headers: # DEFAULT_REQUEST_HEADERS = { # 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8', # 'Accept-Language': 'en', # } # Configure item pipelines # See http://scrapy.readthedocs.org/en/latest/topics/item-pipeline.html # 11. 定义pipeline处理请求 # ITEM_PIPELINES = { # 'step8_king.pipelines.JsonPipeline': 700, # 'step8_king.pipelines.FilePipeline': 500, # } # 12. 自定义扩展，基于信号进行调用 # Enable or disable extensions # See http://scrapy.readthedocs.org/en/latest/topics/extensions.html # EXTENSIONS = { # # 'step8_king.extensions.MyExtension': 500, # } # 13. 爬虫允许的最大深度，可以通过meta查看当前深度；0表示无深度 # DEPTH_LIMIT = 3 # 14. 爬取时，0表示深度优先Lifo(默认)；1表示广度优先FiFo # 后进先出，深度优先 # DEPTH_PRIORITY = 0 # SCHEDULER_DISK_QUEUE = 'scrapy.squeue.PickleLifoDiskQueue' # SCHEDULER_MEMORY_QUEUE = 'scrapy.squeue.LifoMemoryQueue' # 先进先出，广度优先 # DEPTH_PRIORITY = 1 # SCHEDULER_DISK_QUEUE = 'scrapy.squeue.PickleFifoDiskQueue' # SCHEDULER_MEMORY_QUEUE = 'scrapy.squeue.FifoMemoryQueue' # 15. 调度器队列 # SCHEDULER = 'scrapy.core.scheduler.Scheduler' # from scrapy.core.scheduler import Scheduler # 16. 访问URL去重 # DUPEFILTER_CLASS = 'step8_king.duplication.RepeatUrl' # Enable and configure the AutoThrottle extension (disabled by default) # See http://doc.scrapy.org/en/latest/topics/autothrottle.html """ 17. 自动限速算法 from scrapy.contrib.throttle import AutoThrottle 自动限速设置 1. 获取最小延迟 DOWNLOAD_DELAY 2. 获取最大延迟 AUTOTHROTTLE_MAX_DELAY 3. 设置初始下载延迟 AUTOTHROTTLE_START_DELAY 4. 当请求下载完成后，获取其"连接"时间 latency，即：请求连接到接受到响应头之间的时间 5. 用于计算的... AUTOTHROTTLE_TARGET_CONCURRENCY target_delay = latency / self.target_concurrency new_delay = (slot.delay + target_delay) / 2.0 # 表示上一次的延迟时间 new_delay = max(target_delay, new_delay) new_delay = min(max(self.mindelay, new_delay), self.maxdelay) slot.delay = new_delay """ # 开始自动限速 # AUTOTHROTTLE_ENABLED = True # The initial download delay # 初始下载延迟 # AUTOTHROTTLE_START_DELAY = 5 # The maximum download delay to be set in case of high latencies # 最大下载延迟 # AUTOTHROTTLE_MAX_DELAY = 10 # The average number of requests Scrapy should be sending in parallel to each remote server # 平均每秒并发数 # AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0 # Enable showing throttling stats for every response received: # 是否显示 # AUTOTHROTTLE_DEBUG = True # Enable and configure HTTP caching (disabled by default) # See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings """ 18. 启用缓存 目的用于将已经发送的请求或相应缓存下来，以便以后使用 from scrapy.downloadermiddlewares.httpcache import HttpCacheMiddleware from scrapy.extensions.httpcache import DummyPolicy from scrapy.extensions.httpcache import FilesystemCacheStorage """ # 是否启用缓存策略 # HTTPCACHE_ENABLED = True # 缓存策略：所有请求均缓存，下次在请求直接访问原来的缓存即可 # HTTPCACHE_POLICY = "scrapy.extensions.httpcache.DummyPolicy" # 缓存策略：根据Http响应头：Cache-Control、Last-Modified 等进行缓存的策略 # HTTPCACHE_POLICY = "scrapy.extensions.httpcache.RFC2616Policy" # 缓存超时时间 # HTTPCACHE_EXPIRATION_SECS = 0 # 缓存保存路径 # HTTPCACHE_DIR = 'httpcache' # 缓存忽略的Http状态码 # HTTPCACHE_IGNORE_HTTP_CODES = [] # 缓存存储的插件 # HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage' """ 19. 代理，需要在环境变量中设置 from scrapy.contrib.downloadermiddleware.httpproxy import HttpProxyMiddleware 方式一：使用默认 os.environ { http_proxy:http://root:woshiniba@192.168.11.11:9999/ https_proxy:http://192.168.11.11:9999/ } 方式二：使用自定义下载中间件 def to_bytes(text, encoding=None, errors='strict'): if isinstance(text, bytes): return text if not isinstance(text, six.string_types): raise TypeError('to_bytes must receive a unicode, str or bytes ' 'object, got %s' % type(text).__name__) if encoding is None: encoding = 'utf-8' return text.encode(encoding, errors) class ProxyMiddleware(object): def process_request(self, request, spider): PROXIES = [ {'ip_port': '111.11.228.75:80', 'user_pass': ''}, {'ip_port': '120.198.243.22:80', 'user_pass': ''}, {'ip_port': '111.8.60.9:8123', 'user_pass': ''}, {'ip_port': '101.71.27.120:80', 'user_pass': ''}, {'ip_port': '122.96.59.104:80', 'user_pass': ''}, {'ip_port': '122.224.249.122:8088', 'user_pass': ''}, ] proxy = random.choice(PROXIES) if proxy['user_pass'] is not None: request.meta['proxy'] = to_bytes（"http://%s" % proxy['ip_port']） encoded_user_pass = base64.encodestring(to_bytes(proxy['user_pass'])) request.headers['Proxy-Authorization'] = to_bytes('Basic ' + encoded_user_pass) print "**************ProxyMiddleware have pass************" + proxy['ip_port'] else: print "**************ProxyMiddleware no pass************" + proxy['ip_port'] request.meta['proxy'] = to_bytes("http://%s" % proxy['ip_port']) DOWNLOADER_MIDDLEWARES = { 'step8_king.middlewares.ProxyMiddleware': 500, } """ """ 20. Https访问 Https访问时有两种情况： 1. 要爬取网站使用的可信任证书(默认支持) DOWNLOADER_HTTPCLIENTFACTORY = "scrapy.core.downloader.webclient.ScrapyHTTPClientFactory" DOWNLOADER_CLIENTCONTEXTFACTORY = "scrapy.core.downloader.contextfactory.ScrapyClientContextFactory" 2. 要爬取网站使用的自定义证书 DOWNLOADER_HTTPCLIENTFACTORY = "scrapy.core.downloader.webclient.ScrapyHTTPClientFactory" DOWNLOADER_CLIENTCONTEXTFACTORY = "step8_king.https.MySSLFactory" # https.py from scrapy.core.downloader.contextfactory import ScrapyClientContextFactory from twisted.internet.ssl import (optionsForClientTLS, CertificateOptions, PrivateCertificate) class MySSLFactory(ScrapyClientContextFactory): def getCertificateOptions(self): from OpenSSL import crypto v1 = crypto.load_privatekey(crypto.FILETYPE_PEM, open('/Users/wupeiqi/client.key.unsecure', mode='r').read()) v2 = crypto.load_certificate(crypto.FILETYPE_PEM, open('/Users/wupeiqi/client.pem', mode='r').read()) return CertificateOptions( privateKey=v1, # pKey对象 certificate=v2, # X509对象 verify=False, method=getattr(self, 'method', getattr(self, '_ssl_method', None)) ) 其他： 相关类 scrapy.core.downloader.handlers.http.HttpDownloadHandler scrapy.core.downloader.webclient.ScrapyHTTPClientFactory scrapy.core.downloader.contextfactory.ScrapyClientContextFactory 相关配置 DOWNLOADER_HTTPCLIENTFACTORY DOWNLOADER_CLIENTCONTEXTFACTORY """ """ 21. 爬虫中间件 class SpiderMiddleware(object): def process_spider_input(self,response, spider): ''' 下载完成，执行，然后交给parse处理 :param response: :param spider: :return: ''' pass def process_spider_output(self,response, result, spider): ''' spider处理完成，返回时调用 :param response: :param result: :param spider: :return: 必须返回包含 Request 或 Item 对象的可迭代对象(iterable) ''' return result def process_spider_exception(self,response, exception, spider): ''' 异常调用 :param response: :param exception: :param spider: :return: None,继续交给后续中间件处理异常；含 Response 或 Item 的可迭代对象(iterable)，交给调度器或pipeline ''' return None def process_start_requests(self,start_requests, spider): ''' 爬虫启动时调用 :param start_requests: :param spider: :return: 包含 Request 对象的可迭代对象 ''' return start_requests 内置爬虫中间件： 'scrapy.contrib.spidermiddleware.httperror.HttpErrorMiddleware': 50, 'scrapy.contrib.spidermiddleware.offsite.OffsiteMiddleware': 500, 'scrapy.contrib.spidermiddleware.referer.RefererMiddleware': 700, 'scrapy.contrib.spidermiddleware.urllength.UrlLengthMiddleware': 800, 'scrapy.contrib.spidermiddleware.depth.DepthMiddleware': 900, """ # from scrapy.contrib.spidermiddleware.referer import RefererMiddleware # Enable or disable spider middlewares # See http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html SPIDER_MIDDLEWARES = { # 'step8_king.middlewares.SpiderMiddleware': 543, } """ 22. 下载中间件 class DownMiddleware1(object): def process_request(self, request, spider): ''' 请求需要被下载时，经过所有下载器中间件的process_request调用 :param request: :param spider: :return: None,继续后续中间件去下载； Response对象，停止process_request的执行，开始执行process_response Request对象，停止中间件的执行，将Request重新调度器 raise IgnoreRequest异常，停止process_request的执行，开始执行process_exception ''' pass def process_response(self, request, response, spider): ''' spider处理完成，返回时调用 :param response: :param result: :param spider: :return: Response 对象：转交给其他中间件process_response Request 对象：停止中间件，request会被重新调度下载 raise IgnoreRequest 异常：调用Request.errback ''' print('response1') return response def process_exception(self, request, exception, spider): ''' 当下载处理器(download handler)或 process_request() (下载中间件)抛出异常 :param response: :param exception: :param spider: :return: None：继续交给后续中间件处理异常； Response对象：停止后续process_exception方法 Request对象：停止中间件，request将会被重新调用下载 ''' return None 默认下载中间件 { 'scrapy.contrib.downloadermiddleware.robotstxt.RobotsTxtMiddleware': 100, 'scrapy.contrib.downloadermiddleware.httpauth.HttpAuthMiddleware': 300, 'scrapy.contrib.downloadermiddleware.downloadtimeout.DownloadTimeoutMiddleware': 350, 'scrapy.contrib.downloadermiddleware.useragent.UserAgentMiddleware': 400, 'scrapy.contrib.downloadermiddleware.retry.RetryMiddleware': 500, 'scrapy.contrib.downloadermiddleware.defaultheaders.DefaultHeadersMiddleware': 550, 'scrapy.contrib.downloadermiddleware.redirect.MetaRefreshMiddleware': 580, 'scrapy.contrib.downloadermiddleware.httpcompression.HttpCompressionMiddleware': 590, 'scrapy.contrib.downloadermiddleware.redirect.RedirectMiddleware': 600, 'scrapy.contrib.downloadermiddleware.cookies.CookiesMiddleware': 700, 'scrapy.contrib.downloadermiddleware.httpproxy.HttpProxyMiddleware': 750, 'scrapy.contrib.downloadermiddleware.chunked.ChunkedTransferMiddleware': 830, 'scrapy.contrib.downloadermiddleware.stats.DownloaderStats': 850, 'scrapy.contrib.downloadermiddleware.httpcache.HttpCacheMiddleware': 900, } """ # from scrapy.contrib.downloadermiddleware.httpauth import HttpAuthMiddleware # Enable or disable downloader middlewares # See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html # DOWNLOADER_MIDDLEWARES = { # 'step8_king.middlewares.DownMiddleware1': 100, # 'step8_king.middlewares.DownMiddleware2': 500, # }
Scrapy自定义扩展
Scrapy使用信号来通知事情发生。您可以在您的Scrapy项目中捕捉一些信号(使用 extension)来完成额外的工作或添加额外的功能，扩展Scrapy。
from scrapy import signals class MyExtension(object): def __init__(self, value): self.value = value @classmethod def from_crawler(cls, crawler): val = crawler.settings.getint('MMMM') ext = cls(val) crawler.signals.connect(ext.spider_opened, signal=signals.spider_opened) crawler.signals.connect(ext.spider_closed, signal=signals.spider_closed) return ext def spider_opened(self, spider): print('open') def spider_closed(self, spider): print('close')
更多信号API http://scrapy-chs.readthedocs.io/zh_CN/latest/topics/api.html#module-scrapy.signalmanager
Scrapy源码剖析及自定义Scrapy框架
详细参见>>> https://www.cnblogs.com/zhangliang91/p/10547704.html
